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Author |
Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez |
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Title |
Interpretation of Complex Situations in a Semantic-based Surveillance Framework |
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2008 |
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Signal Processing: Image Communication, Special Issue on Semantic Analysis for Interactive Multimedia Services |
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23 |
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7 |
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554-569 |
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Cognitive vision system; Situation analysis; Applied ontologies |
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The integration of cognitive capabilities in computer vision systems requires both to enable high semantic expressiveness and to deal with high computational costs as large amounts of data are involved in the analysis. This contribution describes a cognitive vision system conceived to automatically provide high-level interpretations of complex real-time situations in outdoor and indoor scenarios, and to eventually maintain communication with casual end users in multiple languages. The main contributions are: (i) the design of an integrative multilevel architecture for cognitive surveillance purposes; (ii) the proposal of a coherent taxonomy of knowledge to guide the process of interpretation, which leads to the conception of a situation-based ontology; (iii) the use of situational analysis for content detection and a progressive interpretation of semantically rich scenes, by managing incomplete or uncertain knowledge, and (iv) the use of such an ontological background to enable multilingual capabilities and advanced end-user interfaces. Experimental results are provided to show the feasibility of the proposed approach. |
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ISE @ ise @ FBR2008 |
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954 |
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Carles Fernandez; Xavier Roca; Jordi Gonzalez |
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Title |
Providing Automatic Multilingual Text Generation to Artificial Cognitive Systems |
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2008 |
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ISE @ ise @ FRG2008 |
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1021 |
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Author |
Jordi Gonzalez; Dani Rowe; J. Varona; Xavier Roca |
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Title |
Understanding Dynamic Scenes based on Human Sequence Evaluation |
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Journal Article |
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Year |
2009 |
Publication |
Image and Vision Computing |
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IMAVIS |
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27 |
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10 |
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1433–1444 |
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Image Sequence Evaluation; High-level processing of monitored scenes; Segmentation and tracking in complex scenes; Event recognition in dynamic scenes; Human motion understanding; Human behaviour interpretation; Natural-language text generation; Realistic demonstrators |
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In this paper, a Cognitive Vision System (CVS) is presented, which explains the human behaviour of monitored scenes using natural-language texts. This cognitive analysis of human movements recorded in image sequences is here referred to as Human Sequence Evaluation (HSE) which defines a set of transformation modules involved in the automatic generation of semantic descriptions from pixel values. In essence, the trajectories of human agents are obtained to generate textual interpretations of their motion, and also to infer the conceptual relationships of each agent w.r.t. its environment. For this purpose, a human behaviour model based on Situation Graph Trees (SGTs) is considered, which permits both bottom-up (hypothesis generation) and top-down (hypothesis refinement) analysis of dynamic scenes. The resulting system prototype interprets different kinds of behaviour and reports textual descriptions in multiple languages. |
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ISE @ ise @ GRV2009 |
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1211 |
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Jordi Gonzalez; J. Varona; Xavier Roca; Juan J. Villanueva |
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Title |
A Comparison Framework for Walking Performances using aSpaces |
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2005 |
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Electronic Letters on Computer Vision and Image Analysis, Special Issue on articulated Motion, 5(3):105–116 (Electronic Letters: IF: 1.016) |
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ISE @ ise @ GVR2005 |
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623 |
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Author |
V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich |
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Title |
Adaptive Correlation Filters for Pattern Recognition |
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2006 |
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Pattern Recognition and Image Analysis |
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16 |
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3 |
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425-431 |
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Pattern recognition, Correlation filters, A adaptive filters |
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Adaptive correlation filters based on synthetic discriminant functions (SDFs) for reliable pattern recognition are proposed. A given value of discrimination capability can be achieved by adapting a SDF filter to the input scene. This can be done by iterative training. Computer simulation results obtained with the proposed filters are compared with those of various correlation filters in terms of recognition performance. |
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ISE @ ise @ KMA2006a |
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673 |
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